To work through these examples, you will need the following on your own computer:
Minitab (you have a licence for this via the university)You will need to be either on campus, or connected to the university VPN, to use Minitab due to licensing restrictions.
Our goal is to show how the measured guinea pig tooth growth varies by combination of supplement and supplement dosage. We could approach this in any of several ways, but here we want to treat each supplement as a category or factor, and each dosage as a category or factor. We’d like to see the distribution of measured tooth lengths conditioned on these explanatory variables.
What we’re looking for is a visual representation of the variation in the dataset, for each combination of supplement and dosage. Normally, a 1D scatterplot is a good way to visualise the raw data, with a boxplot/box-and-whisker plot to represent summary statistics.
Click on Open \(\rightarrow\) Open Worksheet, select the toothgrowth.csv data file, and click Open. This will open up the ToothGrowth dataset in Minitab.
Figure 1.1: Open the ToothGrowth dataset
Figure 1.2: Open the ToothGrowth dataset
Click on Graphs \(\rightarrow\) Boxplot \(\rightarrow\) Single Y Variable \(\rightarrow\) With Groups.
Figure 1.3: Select graph type
Figure 1.4: Select graph type
Then choose the appropriate \(x\)- (group) and \(y\)-variables. We want to see the \(y\)-variable (dependent variable) len, conditioned on the groups: VC and OJ (supp) split by their dosage dose, and we select accordingly.
Figure 1.5: Select boxplot groups
This gives us a similar plot to that we obtained with Excel, showing the same trends with dosage for both supplements, and the same outlier information.
Figure 1.6: Create the boxplot
Minitab plot labels the \(x\)- and \(y\)-axes clearly and correctly.Minitab plot does not add distracting colourMinitab plot does not show the mean for each groupThere are relatively few options to improve the graph, visually, but we can retitle the plot by double-clicking on it, and there are options for adding a little more explanatory data.
Figure 1.7: Annotate and retitle the boxplot
Figure 1.8: Annotate and retitle the boxplot